Parent initiated prednisolone for acute asthma in children of school age: randomised controlled crossover trial

Objective To evaluate the efficacy of a short course of parent initiated oral prednisolone for acute asthma in children of school age

Thermal and magnetic properties of integrable spin-1 and spin-3/2 chains with applications to real compounds

The ground state and thermodynamic properties of spin-1 and spin-3/2 chains are investigated via exactly solved su(3) and su(4) models with physically motivated chemical potential terms. The analysis involves the Thermodynamic Bethe Ansatz and the High Temperature Expansion (HTE) methods. For the spin-1 chain with large single-ion anisotropy, a gapped phase occurs which is significantly different from the valence-bond-solid Haldane phase. The theoretical curves for the magnetization, susceptibility and specific heat are favourably compared with experimental data for a number of spin-1 chain compounds. For the spin-3/2 chain a degenerate gapped phase exists starting at zero external magnetic field. A middle magnetization plateau can be triggered by the single-ion anisotropy term. Overall, our results lend further weight to the applicability of integrable models to the physics of low-dimensional quantum spin systems. They also highlight the utility of the exact HTE method.Comment: 38 pages, 15 figure

Superconductivity in Cu_xTiSe_2

Charge density waves (CDWs) are periodic modulations of the conduction electron density in solids. They are collective states that arise from intrinsic instabilities often present in low dimensional electronic systems. The layered dichalcogenides are the most well-studied examples, with TiSe_2 one of the first CDW-bearing materials known. The competition between CDW and superconducting collective electronic states at low temperatures has long been held and explored, and yet no chemical system has been previously reported where finely controlled chemical tuning allows this competition to be studied in detail. Here we report how, upon controlled intercalation of TiSe_2 with Cu to yield Cu_xTiSe_2, the CDW transition is continuously suppressed, and a new superconducting state emerges near x = 0.04, with a maximum T_c of 4.15 K found at x = 0.08. Cu_xTiSe_2 thus provides the first opportunity to study the CDW to Superconductivity transition in detail through an easily-controllable chemical parameter, and will provide new insights into the behavior of correlated electron systems.Comment: Accepted to Nature Physic

Beam Test of Silicon Strip Sensors for the ZEUS Micro Vertex Detector

For the HERA upgrade, the ZEUS experiment has designed and installed a high precision Micro Vertex Detector (MVD) using single sided micro-strip sensors with capacitive charge division. The sensors have a readout pitch of 120 microns, with five intermediate strips (20 micron strip pitch). An extensive test program has been carried out at the DESY-II testbeam facility. In this paper we describe the setup developed to test the ZEUS MVD sensors and the results obtained on both irradiated and non-irradiated single sided micro-strip detectors with rectangular and trapezoidal geometries. The performances of the sensors coupled to the readout electronics (HELIX chip, version 2.2) have been studied in detail, achieving a good description by a Monte Carlo simulation. Measurements of the position resolution as a function of the angle of incidence are presented, focusing in particular on the comparison between standard and newly developed reconstruction algorithms.Comment: 41 pages, 21 figures, 2 tables, accepted for publication in NIM

Population-aware Hierarchical Bayesian Domain Adaptation via Multiple-component Invariant Learning

While machine learning is rapidly being developed and deployed in health settings such as influenza prediction, there are critical challenges in using data from one environment in another due to variability in features; even within disease labels there can be differences (e.g. "fever" may mean something different reported in a doctor's office versus in an online app). Moreover, models are often built on passive, observational data which contain different distributions of population subgroups (e.g. men or women). Thus, there are two forms of instability between environments in this observational transport problem. We first harness knowledge from health to conceptualize the underlying causal structure of this problem in a health outcome prediction task. Based on sources of stability in the model, we posit that for human-sourced data and health prediction tasks we can combine environment and population information in a novel population-aware hierarchical Bayesian domain adaptation framework that harnesses multiple invariant components through population attributes when needed. We study the conditions under which invariant learning fails, leading to reliance on the environment-specific attributes. Experimental results for an influenza prediction task on four datasets gathered from different contexts show the model can improve prediction in the case of largely unlabelled target data from a new environment and different constituent population, by harnessing both environment and population invariant information. This work represents a novel, principled way to address a critical challenge by blending domain (health) knowledge and algorithmic innovation. The proposed approach will have a significant impact in many social settings wherein who and where the data comes from matters

De novo transcriptome assembly of sugarcane leaves submitted to prolonged water-deficit stress.

ABSTRACT. Sugarcane production is strongly influenced by drought, which is a limiting factor for agricultural productivity in the world. In this study, the gene expression profiles obtained by de novo assembly of the leaf transcriptome of two sugarcane cultivars that differ in their physiological response to water deficit were evaluated by the RNA-Seq method: drought-tolerant cultivar (SP81-3250) and drought-sensitive cultivar (RB855453). For this purpose, plants were grown in a greenhouse for 60 days and were then submitted to three treatments: control (-0.01 to -0.015 MPa), moderate water deficit (-0.05 to -0.055 MPa), and severe water deficit (-0.075 to -0.08 MPa). The plants were evaluated 30, 60, and 90 days after the beginning of treatment. Sequencing on an Illumina platform (RNA-Seq) generated more than one billion sequences, resulting in 177,509 and 185,153 transcripts for the tolerant and sensitive cultivar, respectively. These transcripts were aligned with sequences from Saccharum spp, Sorghum bicolor, Miscanthus giganteus, and Arabidopsis thaliana available in public databases. The differentially expressed genes detected during the prolonged period of water deficit permit to increase our understanding of the molecular patterns involved in the physiological response of the two cultivars. The tolerant cultivar differentially expressed a larger number of genes at 90 days, while in the sensitive cultivar the number of differentially expressed genes was higher in 30 days. Both cultivars perceived the lack of water, but the tolerant cultivar responded more slowly than the sensitive cultivar. The latter requires rapid activation of different water-deficit stress response mechanisms for its survival. This rapid activation of metabolic pathways in response to water stress does not appear to be the key mechanism of drought tolerance in sugarcane. There is still much to clarify on the molecular and physiological pattern of plants in response to drought.Article gmr16028845

de novo assembly and transcriptome analysis of sugarcane leaves from contrasting varieties submited to prolonged water stress.

Sugarcane is an important crop, major source of sugar and alcohol, accounting for two-thirds of the world's sugar production. In Brazil, the sugarcane culture has expanded to areas with prolonged drought seasons, which is constraining its production. In order to identify genes and molecular process related to sugarcane drought tolerance, we performed de novo assembly and transcriptome analysis of two sugarcane genotypes, one tolerant and other sensitive to water stress, submitted to three water deficit condition (30, 60 and 90 days). The de novo assembly of leaves transcriptome was performed using short reads from Illumina RNA-Seq platform, which produced more than 1 billion reads, which were assembled into 177,509 and 185,153 transcripts sequences for the tolerant and sensitive cultivars, respectively. These transcripts were aligned with Sorghum bicolor, Miscanthus giganteus, Arabidopsis thaliana sequences and sugarcane sequences available in public databases. This analysis allowed the identification of a set of sugarcane genes shared with other species, as well as led to the identification of novel transcripts not cataloged yet. Differential expression analysis between genotypes and among days of water deficit were performed with EdgeR and DESeq. The differentially expressed genes were annotated and categorized using Blast2GO. The terms "enzyme regulator" and "transcription regulator" were highlighted within the differentially expressed genes between the contrasting cultivars, suggesting the importance of gene regulation during water deficit. This study found new molecular patterns, which provided hypotheses on plant response to drought and provided important information about genes involved in drought tolerance response.PAG 2016. Pôster P0792